Innovation occurs across many areas, and compliance professionals need not only to be ready for it but also to embrace it. Join Tom Fox, the Voice of Compliance, as he visits with top innovative minds, thinkers, and creators in the award-winning Innovation in Compliance podcast. In this episode, host Tom visits with Nikunj Bajaj, Co-founder & CEO at TrueFoundry, about enterprise agentic AI infrastructure, governance, and hidden costs most organizations are not accounting for.
Nikunj describes TrueFoundry’s platform as a single control plane for enterprises to build, ship, and govern agentic AI applications, inspired by Meta’s internal ML stack, which he says is about a decade ahead of the rest of the industry. He argues enterprises over-focus on model and tool selection when problem definition and effective use are the real constraints. On governance, he identifies two failure modes: avoiding meaningful use cases entirely to sidestep governance risk, or trying to solve all governance problems up front and never reaching ROI. Successful teams implement application-specific controls iteratively, starting with a few high-value use cases rather than hundreds of low-value ones. He highlights that model inference accounts for only about 20% of total generative AI spend, with the majority of spend concentrated in infrastructure, engineering, and debugging, creating cost-allocation and budget-control challenges for compliance teams. For auditability, he argues that an agent without full decision traces is “a liability with an API key,” and walks through how end-to-end tracing enables audit readiness, faster debugging, and proactive attack detection. He closes by advocating centralized control via a unified AI gateway while enabling federated development and tailoring guardrails to whether your exposure surface is external or internal.
Key highlights:
- Stop Chasing Tools
- Governance vs Speed
- Hidden AI Costs
- Agent Auditability
- Board Level Priorities
Resources:
Connect with Nikunj Bajaj
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